Discussion Papers

Stephan Schmitt, Marcus Stronzik

The role of the general productivity factor in different types of incentive regulations for energy Networks

Nr. 399 / Juli 2015

(Full version only available in German)

Summary

As essential component of the German incentive regulation, the revenues of the network operators are significantly determined by a productivity factor, the so-called general X-factor, which aims at controlling for technical change (frontier shift). In the current discussions on the revision of the regulatory framework of the energy networks some market participants do not only question its absolute level but further challenge its general justification. 

In contrast to cost-based regulations, incentive regulations tend to imitate competition. In a competitive environment firms are forced to realize productivity gains through market pressure and to forward the resulting additional profits to final consumers via lower prices. The general X-factor fulfils exactly this task. It incentivizes productivity gains of the regulated firms and ensures that technological progress is passed to final costumers. 

For incentive regulations in the kind of a price- or revenue-cap, we can show theoretically that the general X-factor can directly be derived from the regulatory formula using the analogy to competitive markets. This implies that its usage is mandatory from a theoretical point of view. The experiences in other countries like Austria, Norway and the Netherlands confirm this finding. 

Ultimately, the question how to capture the frontier shift in incentive-based regulations is not a question of "if" than rather of "how". With regard to the empirical estimation of the general X-factor, we recommend the use of sensitivity analysis due to methodological and data-related uncertainties. First, the calculations should be based on different time intervals. Second, different estimation techniques may be applied (e.g. Malmquist index and index numbers like the Tornquist index) in order to exploit the specific advantages of the different methods. The estimation of different specifications may improve the robustness of the results, which has a positive impact on its validity. The forecast quality may be improved further if the calculations are based on time periods in the past with framework conditions rather comparable to those of the regulatory period, the estimation results are applied to. With regard to the German situation, we therefore recommend to make use of data after the year 1998, which constitutes the starting point of the liberalization of German energy markets. Due to the rolling structure of the German incentive regulation and the beginning of the new regime in 2009 shorter time intervals may be justified. 

Discussion Paper is available for download.

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